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1.
This article presents a spatial cognition analysis technique for automated urban building clustering based on urban morphology and Gestalt theory. The proximity graph is selected to present the urban mrphology. The proximity graph considers the local adjacency among buildings, providing a large degree of freedom in object displacement and aggregation. Then, three principles of Gestalt theories, proximity, similarity, and common directions, are considered to extract potential Gestalt building clusters. Next, the Gestalt features are further characterized with seven indicators, that is, area difference, height difference, similarity difference, orientation difference, linear arrangement difference, interval difference, and oblique degree of arrangement. A support vector machine (SVM)-based approach is employed to extract the Gestalt building clusters. This approach transforms the Gestalt cluster extraction into a supervised discrimination process. The method presents a generalized approach for clustering buildings of a given street block into groups, while maintaining the spatial pattern and adjacency of buildings during the displacement operation. In applications of urban building generalization and three-dimensional (3D) urban panoramic-like view, the method presented in this article adequately preserves the spatial patterns, distributions, and arrangements of urban buildings. Moreover, the final 3D panoramic-like views ensure the accurate appearance of important features and landscapes.  相似文献   

2.
Evaluation is a key step to examine the quality of generalized maps with respect to map requirements. Map generalization facilitates the recognition of pattern generating processes by preserving and highlighting the patterns at smaller scales. This article focuses specifically on the evaluation of building patterns in topographic maps that are generalized from large to mid scales. Currently, there is a lack of knowledge and functionality on automatically evaluating how these patterns are generalized. The issues of the evaluation range from missing formal map requirements on building alignments to missing automated evaluation techniques. This article firstly analyses the requirements (constraints) related to the generalization of building alignments. Then, it focuses on three more specific constraints, i.e. on existence, orientation of alignments and spatial distribution of composing buildings. Later, a three-step approach is proposed to (1) recognize and (2) match alignments from source and generalized datasets and (3) evaluate building alignments in generalized datasets. Besides, many-to-many and partial matching between initial and target alignments is a side effect of generalization, which reduces the reliability of the evaluation results. This article introduces a confidence indicator to document the reliability and to inform intended users (e.g. cartographers) and/or systems about the reliability of evaluation decisions. The effectiveness of our approach is demonstrated by evaluating the alignments in both interactively (manually) generalized maps and automated generalized maps. Finally, we discuss how our approach can be used to control automated generalization and identify further improvements.  相似文献   

3.
Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.  相似文献   

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GIS software applications and other mapping tools enable users to correlate data from multiple layers and gain insight from the resulting visualizations. However, most of these applications only feature basic, monolithic layer compositing techniques. These techniques do not always support users effectively in their tasks, as we observed during interviews with GIS experts. We introduce MapMosaic, a novel approach based on dynamic visual compositing that enables users to interactively create and manipulate local composites of multiple vector and raster map layers, taking into account the semantics and attribute values of objects and fields in the compositing process. We evaluate MapMosaic ’s interaction model against that of QGIS (a widely used desktop GIS) and MAPublisher (a professional cartography tool) using the ‘Cognitive Dimensions’ framework and through an analytical comparison, showing that MapMosaic ’s model is more flexible and can support users more effectively in their tasks. We also report on feedback obtained from experts, which further confirms the potential of this highly dynamic approach to map layer compositing.  相似文献   

6.
基于规则的植被地图综合的研究   总被引:4,自引:1,他引:3  
植被地图综合是专题地图综合的一个特例,需要遵循地理数据综合规则,以解决因表达空问缩小而造成的地物要素间的冲突问题,确保图面上图形表达的合理、清晰和美观;同时植被地图综合也要遵循植被分布自身的规律。该文主要研究和分析影响植被地图综合的主要规则,首先描述植被地图的特征,在此基础上分析讨论影响植被地图综合的主要综合规则,并简要介绍了用于表达综合规则的产生式规则方法,用实例描述了这些规则在植被地图综合各个阶段的应用和结果,以此来反映综合规则在植被地图综合过程中的重要性。  相似文献   

7.
Multi-resolution spatial data always contain the inconsistencies of topological, directional, and metric relations due to measurement methods, data acquisition approaches, and map generalization algorithms. Therefore, checking these inconsistencies is critical for maintaining the integrity of multi-resolution or multi-source spatial data. To date, research has focused on the topological consistency, while the directional consistency at different resolutions has been largely overlooked. In this study we developed computation methods to derive the direction relations between coarse spatial objects from the relations between detailed objects. Then, the consistency of direction relations at different resolutions can be evaluated by checking whether the derived relations are compatible with the relations computed from the coarse objects in multi-resolution spatial data. The methods in this study modeled explicitly the scale effects of direction relations induced by the map generalization operator – merging, thus they are efficient for evaluating consistency. The directional consistency is an essential complement to topological and object-based consistencies.  相似文献   

8.
Spatial data uncertainty models (SDUM) are necessary tools that quantify the reliability of results from geographical information system (GIS) applications. One technique used by SDUM is Monte Carlo simulation, a technique that quantifies spatial data and application uncertainty by determining the possible range of application results. A complete Monte Carlo SDUM for generalized continuous surfaces typically has three components: an error magnitude model, a spatial statistical model defining error shapes, and a heuristic that creates multiple realizations of error fields added to the generalized elevation map. This paper introduces a spatial statistical model that represents multiple statistics simultaneously and weighted against each other. This paper's case study builds a SDUM for a digital elevation model (DEM). The case study accounts for relevant shape patterns in elevation errors by reintroducing specific topological shapes, such as ridges and valleys, in appropriate localized positions. The spatial statistical model also minimizes topological artefacts, such as cells without outward drainage and inappropriate gradient distributions, which are frequent problems with random field-based SDUM. Multiple weighted spatial statistics enable two conflicting SDUM philosophies to co-exist. The two philosophies are ‘errors are only measured from higher quality data’ and ‘SDUM need to model reality’. This article uses an automatic parameter fitting random field model to initialize Monte Carlo input realizations followed by an inter-map cell-swapping heuristic to adjust the realizations to fit multiple spatial statistics. The inter-map cell-swapping heuristic allows spatial data uncertainty modelers to choose the appropriate probability model and weighted multiple spatial statistics which best represent errors caused by map generalization. This article also presents a lag-based measure to better represent gradient within a SDUM. This article covers the inter-map cell-swapping heuristic as well as both probability and spatial statistical models in detail.  相似文献   

9.
杨钊  程豪 《地理研究》2019,38(5):1147-1161
随着旅游移民现象不断演变和研究的深入,大量旅游劳工移民在迁入地的半定居和永久性定居行为开始受到国内外学者的关注。中国一些著名的自然观光地因开发早、区域人力资源供给不足等原因,吸引了大量外来企业主的迁入和集聚,因而成为研究旅游企业主移民的合适案例地。本文以黄山汤口为例,以旅游劳工移民中的企业主移民为研究对象,运用回归分析判别移民定居意愿的支持因素,并据此构建结构方程模型,探讨生活满意度、经营满意度、继续经营意愿、社会融合意愿、总体感知对移民定居的影响,进而分析中国自然观光地旅游企业主移民定居驱动机制。研究表明:① 与国外发达经济体旅游企业主移民相比,中国自然观光地旅游企业主移民男性比例明显偏高且更为年轻,其家庭主要收入高度依赖迁移后的工作。经营收益情况是其考虑后续定居的重要前提条件。因此,中国自然观光地旅游企业主移民定居意愿可分为购房定居意愿和退休定居意愿。② 探索性分析表明,中国自然观光地旅游企业主移民的购房定居和退休定居意愿的影响因素包括经营满意因素、生活满意因素、社会融合状况。③ 结构方程模型检验显示,衡量经营目标和动机的总体感知变量对继续经营意愿有替代作用。移民经营满意度是其定居意愿的本质驱动力。④ 社会融合意愿和总体感知构成了购房定居意愿的直接驱动力。除经营满意度外,对居住条件等生活因素的满意与否是购房定居意愿的间接驱动力。⑤ 退休定居意愿最强的直接驱动力是购房定居意愿,总体感知既是其直接弱驱动力又通过购房定居意愿对其产生影响,其余变量均是其间接驱动力。  相似文献   

10.
To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking.  相似文献   

11.
逐层分解选取指标的河系简化方法   总被引:2,自引:1,他引:1  
张青年 《地理研究》2007,26(2):222-228
地图综合理论与方法的研究重点之一,是依据上下文环境进行结构化选取和化简。水系作为地图的基本要素之一,在地图综合中必须依据水系的类型和河网密度进行化简,以保持河网密度差异等宏观特征。本文提出了一种基于支流数量差异的选取指标分配与河系简化方法,将选取数量在河流的各个子流域上按比例分配并递归分配到下一层次的子流域,在各个子流域依据长度和间距选取河流,从而实现顾及密度差异的结构化选取。在软件开发基础上进行了选取试验,并对照手工综合的河系图进行了分析。结果表明,基于支流数量差异的比例选取方法切实可行,能够有效地保持树状河系的特点和河网密度的区域差异。  相似文献   

12.
13.
In every map, irrespective of its theme, objects are represented at a reduced scale. Map contents do not decrease proportionally to the reduction of the map size. Usually an increasing density of the map contents occurs at smaller scales. That is where the generalization plays an important role. Generalization is the process of creating a legible map at a given scale from a more detailed geographical dataset. It is done in such a manner that the character or essence of the original features is retained at successively smaller scales. Though the purposes and benefits of generalization are manifold it is indeed a complex decision-making process which must be intelligently steered by goals and rules from the geographical application domain such that the generalized representation conveys knowledge consistent with the reality. In recent past, lot of work has been done in 2D generalization (Beard, 1991; Weibel, 1995; Bealla, 1995; Ruas and Plazanet, 1996; Sarjakoski and Kilpeläinen, 1999) which defines a set of operations to be performed with the goal to achieve the similar results to those from manual generalization. But 3D generalization is altogether perceived differently. A given 3D urban area mostly consists of roads and buildings. These buildings are of different styles and features. Further the city area may be viewed from different angles and at different heights. So generalization in general and aggregation in particular must deal with all these issues. In this paper, an effort has been made to address these issues.  相似文献   

14.
Topographic maps are powerful tools for the purpose of identifying land use and cover change (LUCC) as they are among the most reliable representations of past landscapes for the time prior to the existence of aerial photography. In light of the increased availability of historical maps, we argue that there is a need for a standardized process to assess map comparability in a systematic way in order to avoid, or at least minimize, the detection of spurious landscape changes due to incompatible map series. A full understanding of map quality, background and error distributions is fundamental to attain reliable LUCC results. The conceptual framework presented in this study considers the context, distortion and cartographic generalization of topographic maps. Furthermore, it includes an approach to homogenize the level of generalization of landscape elements (e.g. forests) from maps with different scales. To demonstrate its application, we assessed the comparability of seven topographic maps from Canton Zurich covering a time span of 336 years (1664–2000). Overall, for the maps of Canton Zurich, a wall-to-wall comparison of forest cover based on the topographic maps presented here can be problematic for the oldest map from 1664. Based on the results, a wall-to-wall comparison with the later maps is not recommended, due to its substantial distortion. Yet, after re-generalization of natural landscape elements, such as forests, a comparison based on landscape indices is possible, even for the oldest map. Furthermore, our results demonstrate that maps from the mid-19th century onward possess an acceptable level of accuracy. This framework can be applied to a wide range of maps at regional, national, or global levels, providing the opportunity to look at land cover history over multiple centuries.  相似文献   

15.
街网约束下的城市居民地自动综合算法   总被引:2,自引:0,他引:2  
街网约束下的城市居民地自动综合是地图综合中的一个难点,该文从居民地多边形化简、居民地合并等方面讨论街网约束下城市居民地自动综合算法,并研究综合操作后居民地与街道冲突的解决方法.由此实现的城市居民地自动综合功能用于实验数据中,对多边形形态的化简、合并及街道形态的保持都较无约束条件下的居民地综合更合理.  相似文献   

16.
遥感影象中居民地信息的自动提取与制图   总被引:11,自引:2,他引:9  
如何自动获得居民地矢量信息是遥感和地理信息系统领域研究的热点问题。以南京市江宁区为研究区域,基于光谱特征分析,建立决策树模型进行居民地信息的自动提取。重点研究如何将已提取的居民地图斑进行形态综合,得到满足地理信息系统数据建库与更新、遥感制图等的可视化图形数据,为灾害评估、城镇扩展和环境变化研究等提供必要的基础信息。最后,给出文章方法的实验结果并做出讨论。  相似文献   

17.
分析传统网络地理信息系统(WebGIS)体系的弊端,从负载均衡与地图状态同步的角度提出一种基于服务器场的分布式WebGIS计算模型。通过自定义服务器场底层交互协议、地图服务器场分布式动态均衡调度算法、地图状态对象池技术,解决了传统WebGIS计算模型异构兼容性差、并行处理能力弱、地图状态对象无法同步等问题,并建立试验床对该模型的性能进行验证。  相似文献   

18.
19.
孟祥锐  张树清  臧淑英 《地理科学》2018,38(11):1914-1923
以洪河国家级自然保护区为研究对象,应用卷积神经网络(CNN)方法进行高分辨率湿地遥感影像的分类研究,并与基于光谱支持向量机(SP-SVM)的方法和基于纹理及光谱的支持向量机(TSP-SVM)的方法进行了对比。结果显示,对于所选取的2个研究区域,CNN分类方法的全局精度高于SP-SVM方法5.61%和5%,高于TSP-SVM方法4.18%和4.15%。尤其对于部分湿地植被的分类精度明显高于SP-SVM和TSP-SVM方法。研究表明,卷积神经网络为湿地识别的精细划分提供了有利的手段。  相似文献   

20.
Building generalization is a difficult operation due to the complexity of the spatial distribution of buildings and for reasons of spatial recognition. In this study, building generalization is decomposed into two steps, i.e. building grouping and generalization execution. The neighbourhood model in urban morphology provides global constraints for guiding the global partitioning of building sets on the whole map by means of roads and rivers, by which enclaves, blocks, superblocks or neighbourhoods are formed; whereas the local constraints from Gestalt principles provide criteria for the further grouping of enclaves, blocks, superblocks and/or neighbourhoods. In the grouping process, graph theory, Delaunay triangulation and the Voronoi diagram are employed as supporting techniques. After grouping, some useful information, such as the sum of the building's area, the mean separation and the standard deviation of the separation of buildings, is attached to each group. By means of the attached information, an appropriate operation is selected to generalize the corresponding groups. Indeed, the methodology described brings together a number of well-developed theories/techniques, including graph theory, Delaunay triangulation, the Voronoi diagram, urban morphology and Gestalt theory, in such a way that multiscale products can be derived.  相似文献   

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